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This study investigated the correlation of the extent of chromosomal aberrations including uniparental disomies (UPDs) by SNP-chip analysis and FISH to telomere length in 46 patients with CLL. CLL harboring high risk aberrations, i.e. deletions of 11q22-23 or 17p13, had significantly shorter telomeres (higher ΔTL) compared to patients with CLL without such abnormalities. Patients with high chromosomal aberration rates had a worse overall survival compared to cases with lower aberration rates. Interestingly, however, an increase was found in the number of UPDs with shorter telomeres. These findings support the idea that telomeres in CLL cells play a role in the overall chromosome stability and could be involved in the occurrence of UPDs.

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Importance: Although rheumatic heart disease has been nearly eradicated in high-income countries, 3 in 4 children grow up in parts of the world where it is still endemic. Objectives: To determine the prevalence of clinically silent and manifest rheumatic heart disease as a function of age, sex, and socioeconomic status and to estimate age-specific incidence. Design, Setting, and Participants: In this school-based cross-sectional study with cluster sampling, 26 schools in the Sunsari district in Eastern Nepal with 5467 eligible children 5 to 15 years of age were randomly selected from 595 registered schools. After exclusion of 289 children, 5178 children were enrolled in the present study from December 12, 2012, through September 12, 2014. Data analysis was performed from October 1, 2014, to April 15, 2015. Exposures: Demographic and socioeconomic characteristics were acquired in a standardized interview by means of a questionnaire customized to the age of the children. A focused medical history was followed by a brief physical examination. Cardiac auscultation and transthoracic echocardiography were performed by 2 independent physicians. Main Outcomes and Measures: Rheumatic heart disease according to the World Heart Federation criteria. Results: The median age of the 5178 children enrolled in the study was 10 years (interquartile range, 8-13 years), and 2503 (48.3%) were female. The prevalence of borderline or definite rheumatic heart disease was 10.2 (95% CI, 7.5-13.0) per 1000 children and increased with advancing age from 5.5 (95% CI, 3.5-7.5) per 1000 children 5 years of age to 16.0 (95% CI, 14.9-17.0) in children 15 years of age, whereas the mean incidence remained stable at 1.1 per 1000 children per year. Children with rheumatic heart disease were older than children without rheumatic heart disease (median age [interquartile range], 11 [9-14] years vs 10 [8-13] years; P = .03), more commonly female (34 [64.2%] vs 2469 [48.2%]; P = .02), and more frequently went to governmental schools (40 [75.5%] vs 2792 [54.5%]; P = .002). Silent disease (n = 44) was 5 times more common than manifest disease (n = 9). Conclusions and Relevance: Rheumatic heart disease affects 1 in 100 schoolchildren in Eastern Nepal, is primarily clinically silent, and may be more common among girls. The overall prevalence and the ratio of manifest to subclinical disease increase with advancing age, whereas the incidence remains stable at 1.1 per 1000 children per year. Early detection of silent disease may help prevent progression to severe valvular damage.

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The ice cover of the Arctic Ocean has been changing dramatically in the last decades and the consequences for the sea-ice associated ecosystem remain difficult to assess. Algal aggregates underneath sea ice have been described sporadically but the frequency and distribution of their occurrence is not well quantified. We used upward looking images obtained by a remotely operated vehicle (ROV) to derive estimates of ice algal aggregate biomass and to investigate their spatial distribution. During the IceArc expedition (ARK-XXVII/3) of RV Polarstern in late summer 2012, different types of algal aggregates were observed floating underneath various ice types in the Central Arctic basins. Our results show that the floe scale distribution of algal aggregates in late summer is very patchy and determined by the topography of the ice underside, with aggregates collecting in dome shaped structures and at the edges of pressure ridges. The buoyancy of the aggregates was also evident from analysis of the aggregate size distribution. Different approaches used to estimate aggregate biomass yield a wide range of results. This highlights that special care must be taken when upscaling observations and comparing results from surveys conducted using different methods or on different spatial scales.

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The amount of solar radiation transmitted through Arctic sea ice is determined by the thickness and physical properties of snow and sea ice. Light transmittance is highly variable in space and time since thickness and physical properties of snow and sea ice are highly heterogeneous on variable time and length scales. We present field measurements of under-ice irradiance along transects under undeformed land-fast sea ice at Barrow, Alaska (March, May, and June 2010). The measurements were performed with a spectral radiometer mounted on a floating under-ice sled. The objective was to quantify the spatial variability of light transmittance through snow and sea ice, and to compare this variability along its seasonal evolution. Along with optical measurements, snow depth, sea ice thickness, and freeboard were recorded, and ice cores were analyzed for chlorophyll a and particulate matter. Our results show that snow cover variability prior to onset of snow melt causes as much relative spatial variability of light transmittance as the contrast of ponded and white ice during summer. Both before and after melt onset, measured transmittances fell in a range from one third to three times the mean value. In addition, we found a twentyfold increase of light transmittance as a result of partial snowmelt, showing the seasonal evolution of transmittance through sea ice far exceeds the spatial variability. However, prior melt onset, light transmittance was time invariant and differences in under-ice irradiance were directly related to the spatial variability of the snow cover.